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Ant-based distributed protocol for coordination of a swarm of robots in demining mission

机译:基于蚂蚁的分布式协议,用于协调一群机器人在排雷任务中

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Coordination among multiple robots has been extensively studied, since a number of practical real problem s can be performed using an effective approach. In this paper is investigated a collective task that requires a multi-robot system to search for randomly distributed mines in an unknown environment and disarm them cooperatively. The communication among the swarm of robots influences the overall performance in terms of time to execute the task or consumed energy. To address this problem, a new distributed recruiting protocol to coordinate a swarm of robots in demining mission, is described. This problem is a multi-objective problem and two bio inspired strategies are used. The novelty of this approach lies in the combination of direct and indirect communication: on one hand an indirect communication among robots is used for the exploration of the environment, on the other hand a novel protocol is used to accomplish the recruiting and coordination of the robots for demining task. This protocol attempts to tackle the question of how autonomous robot can coordinate themselves into an unknown environment relying on simple low-level capabilities. The strategy is able to adapt the current system dynamics if the number of robots or the environment structure or both change. The proposed approach has been implemented and has been evaluated in several simulated environments. We analyzed the impact of our approach in the overall performance of a robot team. Experimental results indicated the effectiveness and efficiency of the proposed protocol to spread the robots in the environment.
机译:多个机器人之间的协调已经广泛研究,因为可以使用有效方法执行许多实际的真实问题。在本文中,调查了一个集体任务,该任务需要一个多机器人系统,以在未知环境中搜索随机分布的地雷,并配对它们的协作。机器人的沟通在时间来执行任务或消耗能量方面的整体性能。为了解决这个问题,描述了一种新的分布式招聘协议,用于在排雷任务中协调一群机器人。这个问题是一个多目标问题,使用了两个生物启发策略。这种方法的新颖性在于直接和间接通信的组合:一方面,机器人之间的间接通信用于探索环境,另一方面,一种新颖的协议用于实现机器人的招聘和协调。用于排雷任务。该协议尝试解决自主机器人如何将自己协调为依赖于简单的低级功能的未知环境的问题。如果机器人的数量或环境结构或两个变化,该策略能够调整当前系统动态。已经实施了所提出的方法,并在若干模拟环境中进行了评估。我们分析了我们对机器人团队整体表现的影响。实验结果表明,拟议议定书的效力和效率在环境中传播机器人。

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